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Combined Cumulative AI Model Releases

Run the Combined Cumulative AI Model Releases MicroSim Fullscreen

About This MicroSim

This line chart plots the running total of major AI model releases across 11 frontier AI labs (OpenAI, Anthropic, Google, Meta, SpaceXAI, DeepSeek, Mistral, Moonshot AI, Z.ai, Qwen, and NVIDIA), month by month since ChatGPT launched in November 2022. It replicates the "Combined Cumulative Releases Over Time" chart from AI Release Tracker.

Where the AI Model Releases by Year chart shows the rate of releases, this chart shows the compounding effect: the curve visibly steepens each year, illustrating why the AI field feels like it is accelerating rather than growing at a steady pace.

How to Use

Hover anywhere on the line to see the exact cumulative total as of that month. The curve reaches 249 releases by September 2026.

Iframe Embed Code

You can add this MicroSim to any web page by adding this to your HTML:

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<iframe src="https://dmccreary.github.io/tracking-ai-course/sims/ai-releases-cumulative/main.html"
        height="472px"
        width="100%"
        scrolling="no"></iframe>

Updating the Data

Chart values live in a dataset shared by six MicroSims: ../ai-release-data/data.json. This chart reads the months[].cumulative field, which is precomputed — add a new month to the months array with its cumulative value equal to the previous month's cumulative plus the new month's value. See ../ai-release-data/README.md for the full schema.

These MicroSims share the same dataset:

Lesson Plan

Grade Level

Adult professional / executive education (organizational AI-tracking course)

Duration

5-10 minutes

Prerequisites

None — pairs well with AI Model Releases by Year.

Activities

  1. Exploration (3 min): Have learners trace the curve from 2022 to 2026 and note where it visibly steepens.
  2. Guided Discussion (4 min): Compare this chart to the "AI Model Releases by Year" bar chart — ask learners which view makes the acceleration feel more dramatic, and why.
  3. Assessment (3 min): Ask learners to estimate the cumulative total at the end of 2026 by extrapolating the current slope.

Assessment

Learners should be able to explain the difference between a rate chart (releases per year) and a cumulative chart (running total), and why both are useful for tracking AI capability growth.

References

  1. AI Release Tracker — Analytics — source of the underlying release-count data.
  2. Chart.js Documentation — charting library used to build this MicroSim.